import coremltools
coreml_model = coremltools.converters.caffe.convert(
    ('train_squeezenet_mirror_rot_trainval_manual_p2__iter_1000.caffemodel', 'deploy.prototxt'), is_bgr=True, image_input_names='data', class_labels='class_labels.txt'
)
coreml_model.save('model1000.mlmodel')
coreml_model = coremltools.converters.caffe.convert(
    ('train_squeezenet_scratch_trainval_manual_p2__iter_8000.caffemodel', 'deploy.prototxt'), is_bgr=True, image_input_names='data', class_labels='class_labels.txt'
)
coreml_model.save('model8000.mlmodel')
coreml_model = coremltools.converters.caffe.convert(
    ('train_squeezenet_trainval_manual_p2__iter_3817.caffemodel', 'deploy.prototxt'), is_bgr=True, image_input_names='data', class_labels='class_labels.txt'
)
coreml_model.save('model3817.mlmodel')